Lecture Notes in Data Mining.

Contains lectures which explore in depth the core of data mining (classification, clustering and association rules) by offering overviews that include both analysis and insight.

This work lays a framework of data mining techniques by explaining some of the basics such as applications of Bayes Theorem, similarity measures, and decision trees.